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CourseEnergy and Networks Enrolment open

Course on Autonomous Robots for Nuclear Inspection

Online course of 300 h in Autonomous Robots for Nuclear Inspection. 6 modules covering UL 4600 (safety of autonomous products), IEEE 7001 (transparency of autonomous systems) and ROS 2 (Nav2). Dedicated tutor and enrolment open.

Duration300 h
ModeOnline
Start datesOctober / March
LocationEurope (Madrid)
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Describe autonomous robotic platforms for inspection.

02

Implement simultaneous localisation and mapping algorithms.

03

Plan inspection trajectories in structured environments.

04

Integrate radiological, thermal and visual sensors.

05

Apply machine vision to anomaly detection.

06

Evaluate the safety and transparency of autonomous systems.

07

Design an autonomous inspection mission for an academic case.

Profile

Who it's for

  • Autonomous robotics engineer looking to specialise in Autonomous Robots for Nuclear Inspection.
  • Nuclear inspection engineer looking to specialise in Autonomous Robots for Nuclear Inspection.
  • Perception and SLAM engineer looking to specialise in Autonomous Robots for Nuclear Inspection.
  • ROS developer looking to specialise in Autonomous Robots for Nuclear Inspection.
  • Machine vision engineer looking to specialise in Autonomous Robots for Nuclear Inspection.
  • Service robotics researcher looking to specialise in Autonomous Robots for Nuclear Inspection.
  • Engineering or science graduates looking to move into the nuclear industry.
Standards & tools

What you'll work with

  • UL 4600 (safety of autonomous products)
  • IEEE 7001 (transparency of autonomous systems)
  • IEC 61508 (functional safety)
  • ISO 18646-2 (navigation performance of service robots)
  • ISO 8373 (robotics vocabulary)
  • IAEA GSR Part 3 (radiation protection)
Syllabus

6 modules · 300 h

  1. 1.1In-service inspection programmes
  2. 1.2ASME Section XI
  3. 1.3Hard-to-reach and high-dose areas
  4. 1.4Containment, steam generators and reactor vessel
  5. 1.5Inspection of cables and piping
  6. 1.6Operator rounds and surveillance
  7. 1.7Benefits of autonomy
  8. 1.8Experience with quadruped robots in power plants
  9. 1.9Availability requirements
  10. 1.10Case study: identifying rounds that can be automated
  1. 2.1Quadruped robots
  2. 2.2Wheeled and tracked robots
  3. 2.3Indoor drones
  4. 2.4Magnetic climbing robots
  5. 2.5Robots for steam generators
  6. 2.6Snake-type robots
  7. 2.7Radiation hardening
  8. 2.8Power autonomy and charging stations
  9. 2.9Mechanical design for industrial environments
  10. 2.10Workshop: comparing platforms for an inspection round
  1. 3.1Simultaneous localisation and mapping
  2. 3.2Global and local planning
  3. 3.3Stairs and obstacles
  4. 3.4Semantic plant maps
  5. 3.5GNSS-denied indoor navigation
  6. 3.6Collision avoidance with people
  7. 3.7ROS 2 and Nav2
  8. 3.8Radiation as a cost in planning
  9. 3.9Recovery from loss of localisation
  10. 3.10Lab: autonomous mission with Nav2 in simulation
  1. 4.1Automatic gauge reading
  2. 4.2Infrared thermography
  3. 4.3Acoustic leak detection
  4. 4.4Vibration measurement
  5. 4.5Anomaly detection with deep learning
  6. 4.6Radiation mapping
  7. 4.7Robotic non-destructive testing
  8. 4.8Integration with the digital twin
  9. 4.9Automatic report generation
  10. 4.10Practice: reading analogue indicators with machine vision
  1. 5.1Verification of autonomous behaviours
  2. 5.2Functional safety and emergency stops
  3. 5.3Cybersecurity of the robot and the network
  4. 5.4Acceptance by operators
  5. 5.5Qualification and on-site testing
  6. 5.6Fleet maintenance
  7. 5.7Inspection data management
  8. 5.8Value and return indicators
  9. 5.9Applicable regulatory requirements
  10. 5.10Case study: deployment plan at a power plant
  1. 6.1Defining the inspection mission
  2. 6.2Platform and sensor selection
  3. 6.3Map and route planning
  4. 6.4Perception algorithms
  5. 6.5Integration in ROS 2
  6. 6.6Simulation testing
  7. 6.7Reliability analysis
  8. 6.8Evaluation of results
  9. 6.9Report and presentation
  10. 6.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable materials, recorded classes and a dedicated technical tutor. No fixed timetable: students progress at their own pace within the intake period, making it easy to combine with work.

Each module combines theory, guided reading of the original standards and applied exercises. The software used is ROS 2 (Nav2), Gazebo, Python (OpenCV), Cartographer (SLAM), MATLAB, in free, academic or trial versions. Testing is studied through real procedures from autonomous inspection runs on mock-ups, localisation tests and mapping, anomaly detection with machine vision. Assessment is continuous for each module, plus a final capstone project.

Accredited laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, cyber-OT, DIH and compliance as pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Defining the inspection mission

Describe autonomous robotic platforms for inspection.

Platform and sensor selection

Implement simultaneous localisation and mapping algorithms.

Map and route planning

Plan inspection trajectories in structured environments.

Perception algorithms

Integrate radiological, thermal and visual sensors.

Integration in ROS 2

Apply machine vision to anomaly detection.

Career opportunities

Where this takes you

Autonomous robotics engineerNuclear inspection engineerPerception and SLAM engineerROS developerMachine vision engineerService robotics researcher
Admissions & scholarships

Requirements

  • No previous qualification is required.
  • An internet connection and a computer able to run the programme software.
  • A level of English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 300 hours spread over 3 to 5 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

You will work with ROS 2 (Nav2), Gazebo, Python (OpenCV), Cartographer (SLAM), MATLAB. Free, academic or trial versions are used, and your tutor will point out a free alternative where one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the capstone project. It is SEIUM's own qualification, not an official state-accredited degree.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Check the credit recognition policy when you enrol.

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